Пример #1
0
        /// <summary>
        /// Construct an aligner
        /// </summary>
        /// <param name="sequences">input sequences</param>
        /// <param name="kmerLength">positive integer of kmer length</param>
        /// <param name="distanceFunctionName">enum: distance function name</param>
        /// <param name="hierarchicalClusteringMethodName">enum: cluster update method</param>
        /// <param name="profileAlignerMethodName">enum: profile-profile aligner name</param>
        /// <param name="profileFunctionName">enum: profile-profile distance function</param>
        /// <param name="similarityMatrix">similarity matrix</param>
        /// <param name="gapOpenPenalty">negative gapOpenPenalty</param>
        /// <param name="gapExtendPenalty">negative gapExtendPenalty</param>
        /// <param name="numberOfPartitions">the number of partitions in dynamic programming</param>
        /// <param name="degreeOfParallelism">degree of parallelism option for parallel extension</param>
        public PAMSAMMultipleSequenceAligner(
            IList <ISequence> sequences,
            int kmerLength,
            DistanceFunctionTypes distanceFunctionName,
            UpdateDistanceMethodsTypes hierarchicalClusteringMethodName,
            ProfileAlignerNames profileAlignerMethodName,
            ProfileScoreFunctionNames profileFunctionName,
            SimilarityMatrix similarityMatrix,
            int gapOpenPenalty,
            int gapExtendPenalty,
            int numberOfPartitions,
            int degreeOfParallelism)
        {
            Performance.Start();

            if (null == sequences)
            {
                throw new ArgumentNullException("sequences");
            }

            if (sequences.Count == 0)
            {
                throw new ArgumentException("Empty input sequences");
            }

            // Set parallel extension option
            if (degreeOfParallelism <= 0)
            {
                throw new ArgumentException("Invalid parallel degree parameter");
            }
            PAMSAMMultipleSequenceAligner.parallelOption = new ParallelOptions {
                MaxDegreeOfParallelism = degreeOfParallelism
            };

            if (numberOfPartitions <= 0)
            {
                throw new ArgumentException("Invalid number of partition parameter");
            }
            _numberOfPartitions = numberOfPartitions;

            // Validate data type
            _alphabet = sequences[0].Alphabet;
            Parallel.For(1, sequences.Count, PAMSAMMultipleSequenceAligner.parallelOption, i =>
            {
                if (!Alphabets.CheckIsFromSameBase(sequences[i].Alphabet, _alphabet))
                {
                    throw new ArgumentException("Inconsistent sequence alphabet");
                }
            });

            List <String> similarityMatrixDNA = new List <String>();

            similarityMatrixDNA.Add("AmbiguousDNA");

            List <String> similarityMatrixRNA = new List <String>();

            similarityMatrixRNA.Add("AmbiguousRNA");

            List <String> similarityMatrixProtein = new List <String>();

            similarityMatrixProtein.Add("BLOSUM45");
            similarityMatrixProtein.Add("BLOSUM50");
            similarityMatrixProtein.Add("BLOSUM62");
            similarityMatrixProtein.Add("BLOSUM80");
            similarityMatrixProtein.Add("BLOSUM90");
            similarityMatrixProtein.Add("PAM250");
            similarityMatrixProtein.Add("PAM30");
            similarityMatrixProtein.Add("PAM70");

            if (_alphabet is DnaAlphabet)
            {
                if (!similarityMatrixDNA.Contains(similarityMatrix.Name))
                {
                    throw new ArgumentException("Inconsistent similarity matrix");
                }
            }
            else if (_alphabet is ProteinAlphabet)
            {
                if (!similarityMatrixProtein.Contains(similarityMatrix.Name))
                {
                    throw new ArgumentException("Inconsistent similarity matrix");
                }
            }
            else if (_alphabet is RnaAlphabet)
            {
                if (!similarityMatrixRNA.Contains(similarityMatrix.Name))
                {
                    throw new ArgumentException("Inconsistent similarity matrix");
                }
            }
            else
            {
                throw new ArgumentException("Invalid alphabet");
            }

            // Initialize parameters
            _kmerLength                       = kmerLength;
            _distanceFunctionName             = distanceFunctionName;
            _hierarchicalClusteringMethodName = hierarchicalClusteringMethodName;
            _profileAlignerName               = profileAlignerMethodName;
            _profileProfileFunctionName       = profileFunctionName;
            SimilarityMatrix                  = similarityMatrix;
            GapOpenCost                       = gapOpenPenalty;
            GapExtensionCost                  = gapExtendPenalty;

            MsaUtils.SetProfileItemSets(_alphabet);

            Performance.Snapshot("Start Aligning");

            // Work...
            Align(sequences);
        }
Пример #2
0
        /// <summary>
        /// Performs Stage 1, 2, and 3 as described in class description.
        /// </summary>
        /// <param name="inputSequences"></param>
        /// <returns></returns>
        public IList <Bio.Algorithms.Alignment.ISequenceAlignment> Align(IEnumerable <ISequence> inputSequences)
        {
            List <ISequence> sequences = inputSequences.ToList();

            // Initializations
            if (sequences.Count > 0)
            {
                if (ConsensusResolver == null)
                {
                    ConsensusResolver = new SimpleConsensusResolver(_alphabet);
                }
                else
                {
                    ConsensusResolver.SequenceAlphabet = _alphabet;
                }
            }

            // Get ProfileAligner ready
            IProfileAligner profileAligner = null;

            switch (_profileAlignerName)
            {
            case (ProfileAlignerNames.NeedlemanWunschProfileAligner):
                if (_degreeOfParallelism == 1)
                {
                    profileAligner = new NeedlemanWunschProfileAlignerSerial(
                        SimilarityMatrix, _profileProfileFunctionName, GapOpenCost, GapExtensionCost, _numberOfPartitions);
                }
                else
                {
                    profileAligner = new NeedlemanWunschProfileAlignerParallel(
                        SimilarityMatrix, _profileProfileFunctionName, GapOpenCost, GapExtensionCost, _numberOfPartitions);
                }
                break;

            case (ProfileAlignerNames.SmithWatermanProfileAligner):
                if (_degreeOfParallelism == 1)
                {
                    profileAligner = new SmithWatermanProfileAlignerSerial(
                        SimilarityMatrix, _profileProfileFunctionName, GapOpenCost, GapExtensionCost, _numberOfPartitions);
                }
                else
                {
                    profileAligner = new SmithWatermanProfileAlignerParallel(
                        SimilarityMatrix, _profileProfileFunctionName, GapOpenCost, GapExtensionCost, _numberOfPartitions);
                }
                break;

            default:
                throw new ArgumentException("Invalid profile aligner name");
            }

            _alignedSequences = new List <ISequence>(sequences.Count);
            float currentScore = 0;

            // STAGE 1

            Performance.Snapshot("Stage 1");
            // Generate DistanceMatrix
            KmerDistanceMatrixGenerator kmerDistanceMatrixGenerator =
                new KmerDistanceMatrixGenerator(sequences, _kmerLength, _alphabet, _distanceFunctionName);

            // Hierarchical clustering
            IHierarchicalClustering hierarcicalClustering =
                new HierarchicalClusteringParallel
                    (kmerDistanceMatrixGenerator.DistanceMatrix, _hierarchicalClusteringMethodName);

            // Generate Guide Tree
            BinaryGuideTree binaryGuideTree =
                new BinaryGuideTree(hierarcicalClustering);

            // Progressive Alignment
            IProgressiveAligner progressiveAlignerA = new ProgressiveAligner(profileAligner);

            progressiveAlignerA.Align(sequences, binaryGuideTree);

            currentScore = MsaUtils.MultipleAlignmentScoreFunction(progressiveAlignerA.AlignedSequences, SimilarityMatrix, GapOpenCost, GapExtensionCost);
            if (currentScore > _alignmentScoreA)
            {
                _alignmentScoreA   = currentScore;
                _alignedSequencesA = progressiveAlignerA.AlignedSequences;
            }
            if (_alignmentScoreA > _alignmentScore)
            {
                _alignmentScore   = _alignmentScoreA;
                _alignedSequences = _alignedSequencesA;
            }

            if (PAMSAMMultipleSequenceAligner.FasterVersion)
            {
                _alignedSequencesB = _alignedSequencesA;
                _alignedSequencesC = _alignedSequencesA;
                _alignmentScoreB   = _alignmentScoreA;
                _alignmentScoreC   = _alignmentScoreA;
            }
            else
            {
                BinaryGuideTree               binaryGuideTreeB              = null;
                IHierarchicalClustering       hierarcicalClusteringB        = null;
                KimuraDistanceMatrixGenerator kimuraDistanceMatrixGenerator = new KimuraDistanceMatrixGenerator();

                if (PAMSAMMultipleSequenceAligner.UseStageB)
                {
                    // STAGE 2
                    Performance.Snapshot("Stage 2");
                    // Generate DistanceMatrix from Multiple Sequence Alignment

                    int iterateTime = 0;

                    while (true)
                    {
                        ++iterateTime;
                        kimuraDistanceMatrixGenerator.GenerateDistanceMatrix(_alignedSequences);

                        // Hierarchical clustering
                        hierarcicalClusteringB = new HierarchicalClusteringParallel
                                                     (kimuraDistanceMatrixGenerator.DistanceMatrix, _hierarchicalClusteringMethodName);

                        // Generate Guide Tree
                        binaryGuideTreeB = new BinaryGuideTree(hierarcicalClusteringB);

                        BinaryGuideTree.CompareTwoTrees(binaryGuideTreeB, binaryGuideTree);
                        binaryGuideTree = binaryGuideTreeB;

                        // Progressive Alignment
                        IProgressiveAligner progressiveAlignerB = new ProgressiveAligner(profileAligner);
                        progressiveAlignerB.Align(sequences, binaryGuideTreeB);

                        currentScore = MsaUtils.MultipleAlignmentScoreFunction(progressiveAlignerB.AlignedSequences, SimilarityMatrix, GapOpenCost, GapExtensionCost);

                        if (currentScore > _alignmentScoreB)
                        {
                            _alignmentScoreB   = currentScore;
                            _alignedSequencesB = progressiveAlignerB.AlignedSequences;
                            break;
                        }
                        else
                        {
                            break;
                        }
                    }
                    if (_alignmentScoreB > _alignmentScore)
                    {
                        _alignmentScore   = _alignmentScoreB;
                        _alignedSequences = _alignedSequencesB;
                    }
                }
                else
                {
                    binaryGuideTreeB = binaryGuideTree;
                }


                // STAGE 3
                Performance.Snapshot("Stage 3");
                // refinement
                //int maxRefineMentTime = sequences.Count * 2 - 2;
                int maxRefineMentTime = 1;
                if (sequences.Count == 2)
                {
                    maxRefineMentTime = 0;
                }

                int refinementTime = 0;
                _alignedSequencesC = new List <ISequence>(sequences.Count);
                for (int i = 0; i < sequences.Count; ++i)
                {
                    _alignedSequencesC.Add(
                        new Sequence(Alphabets.GetAmbiguousAlphabet(_alphabet),
                                     _alignedSequences[i].ToArray())
                    {
                        ID       = _alignedSequences[i].ID,
                        Metadata = _alignedSequences[i].Metadata
                    });
                }

                List <int>[]        leafNodeIndices            = null;
                List <int>[]        allIndelPositions          = null;
                IProfileAlignment[] separatedProfileAlignments = null;
                List <int>[]        eStrings = null;

                while (refinementTime < maxRefineMentTime)
                {
                    ++refinementTime;
                    Performance.Snapshot("Refinement iter " + refinementTime.ToString());
                    bool needRefinement = false;
                    for (int edgeIndex = 0; edgeIndex < binaryGuideTreeB.NumberOfEdges; ++edgeIndex)
                    {
                        leafNodeIndices = binaryGuideTreeB.SeparateSequencesByCuttingTree(edgeIndex);

                        allIndelPositions = new List <int> [2];

                        separatedProfileAlignments = ProfileAlignment.ProfileExtraction(_alignedSequencesC, leafNodeIndices[0], leafNodeIndices[1], out allIndelPositions);
                        eStrings = new List <int> [2];

                        if (separatedProfileAlignments[0].NumberOfSequences < separatedProfileAlignments[1].NumberOfSequences)
                        {
                            profileAligner.Align(separatedProfileAlignments[0], separatedProfileAlignments[1]);
                            eStrings[0] = profileAligner.GenerateEString(profileAligner.AlignedA);
                            eStrings[1] = profileAligner.GenerateEString(profileAligner.AlignedB);
                        }
                        else
                        {
                            profileAligner.Align(separatedProfileAlignments[1], separatedProfileAlignments[0]);
                            eStrings[0] = profileAligner.GenerateEString(profileAligner.AlignedB);
                            eStrings[1] = profileAligner.GenerateEString(profileAligner.AlignedA);
                        }

                        for (int set = 0; set < 2; ++set)
                        {
                            Parallel.ForEach(leafNodeIndices[set], PAMSAMMultipleSequenceAligner.parallelOption, i =>
                            {
                                //Sequence seq = new Sequence(_alphabet, "");
                                List <byte> seqBytes = new List <byte>();

                                int indexAllIndel = 0;
                                for (int j = 0; j < _alignedSequencesC[i].Count; ++j)
                                {
                                    if (indexAllIndel < allIndelPositions[set].Count && j == allIndelPositions[set][indexAllIndel])
                                    {
                                        ++indexAllIndel;
                                    }
                                    else
                                    {
                                        seqBytes.Add(_alignedSequencesC[i][j]);
                                    }
                                }

                                _alignedSequencesC[i]    = profileAligner.GenerateSequenceFromEString(eStrings[set], new Sequence(Alphabets.GetAmbiguousAlphabet(_alphabet), seqBytes.ToArray()));
                                _alignedSequencesC[i].ID = _alignedSequencesC[i].ID;
                                (_alignedSequencesC[i] as Sequence).Metadata = _alignedSequencesC[i].Metadata;
                            });
                        }

                        currentScore = MsaUtils.MultipleAlignmentScoreFunction(_alignedSequencesC, SimilarityMatrix, GapOpenCost, GapExtensionCost);

                        if (currentScore > _alignmentScoreC)
                        {
                            _alignmentScoreC = currentScore;
                            needRefinement   = true;

                            // recreate the tree
                            kimuraDistanceMatrixGenerator.GenerateDistanceMatrix(_alignedSequencesC);
                            hierarcicalClusteringB = new HierarchicalClusteringParallel
                                                         (kimuraDistanceMatrixGenerator.DistanceMatrix, _hierarchicalClusteringMethodName);

                            binaryGuideTreeB = new BinaryGuideTree(hierarcicalClusteringB);
                            break;
                        }
                    }
                    if (!needRefinement)
                    {
                        refinementTime = maxRefineMentTime;
                        break;
                    }
                }
                if (_alignmentScoreC > _alignmentScore)
                {
                    _alignmentScore   = _alignmentScoreC;
                    _alignedSequences = _alignedSequencesC;
                }
                Performance.Snapshot("Stop Stage 3");
            }

            //just for the purpose of integrating PW and MSA with the same output
            IList <Bio.Algorithms.Alignment.ISequenceAlignment> results = new List <Bio.Algorithms.Alignment.ISequenceAlignment>();

            return(results);
        }
Пример #3
0
        /// <summary>
        /// Construct an aligner and run the alignment.
        /// </summary>
        /// <param name="sequences">input sequences</param>
        /// <param name="kmerLength">positive integer of kmer length</param>
        /// <param name="distanceFunctionName">enum: distance function name</param>
        /// <param name="hierarchicalClusteringMethodName">enum: cluster update method</param>
        /// <param name="profileAlignerMethodName">enum: profile-profile aligner name</param>
        /// <param name="profileFunctionName">enum: profile-profile distance function</param>
        /// <param name="similarityMatrix">similarity matrix</param>
        /// <param name="gapOpenPenalty">negative gapOpenPenalty</param>
        /// <param name="gapExtendPenalty">negative gapExtendPenalty</param>
        /// <param name="numberOfPartitions">the number of partitions in dynamic programming</param>
        /// <param name="degreeOfParallelism">degree of parallelism option for parallel extension</param>
        public PAMSAMMultipleSequenceAligner(
            IList <ISequence> sequences,
            int kmerLength,
            DistanceFunctionTypes distanceFunctionName,
            UpdateDistanceMethodsTypes hierarchicalClusteringMethodName,
            ProfileAlignerNames profileAlignerMethodName,
            ProfileScoreFunctionNames profileFunctionName,
            SimilarityMatrix similarityMatrix,
            int gapOpenPenalty,
            int gapExtendPenalty,
            int numberOfPartitions,
            int degreeOfParallelism)
        {
            Performance.Start();

            if (null == sequences)
            {
                throw new ArgumentNullException("sequences");
            }

            if (sequences.Count == 0)
            {
                throw new ArgumentException("Empty input sequences");
            }

            // Set parallel extension option
            if (degreeOfParallelism <= 0)
            {
                throw new ArgumentException("Invalid parallel degree parameter");
            }

            //_degreeOfParallelism = degreeOfParallelism;
            parallelOption = new ParallelOptions {
                MaxDegreeOfParallelism = degreeOfParallelism
            };

            if (numberOfPartitions <= 0)
            {
                throw new ArgumentException("Invalid number of partition parameter");
            }
            _numberOfPartitions = numberOfPartitions;

            // Assign the alphabet
            SetAlphabet(sequences, similarityMatrix, false);

            // Initialize parameters
            KmerLength                       = kmerLength;
            DistanceFunctionName             = distanceFunctionName;
            HierarchicalClusteringMethodName = hierarchicalClusteringMethodName;
            ProfileAlignerName               = profileAlignerMethodName;
            ProfileProfileFunctionName       = profileFunctionName;
            SimilarityMatrix                 = similarityMatrix;
            GapOpenCost                      = gapOpenPenalty;
            GapExtensionCost                 = gapExtendPenalty;

            MsaUtils.SetProfileItemSets(_alphabet);

            Performance.Snapshot("Start Aligning");

            // Work...
            DoAlignment(sequences);
        }